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Record W2282899483 · doi:10.1158/1535-7163.mct-15-0862

<i>In Vitro</i> and <i>In Vivo</i> Studies of a New Class of Anticancer Molecules for Targeted Radiotherapy of Cancer

2016· article· en· W2282899483 on OpenAlexafffund
Chun-Rong Wang, Javed Mahmood, Qinrong Zhang, Ali Vedadi, Jenny Warrington, Ning Ou, Robert G. Bristow, David A. Jaffray, Qing‐Bin Lu

Bibliographic record

VenueMolecular Cancer Therapeutics · 2016
Typearticle
Languageen
FieldChemistry
TopicFree Radicals and Antioxidants
Canadian institutionsPrincess Margaret Cancer CentreUniversity of TorontoUniversity of Waterloo
FundersCanadian Institutes of Health ResearchOntario Ministry of Research and InnovationNatural Sciences and Engineering Research Council of CanadaOntario Ministry of Research, Innovation and Science
KeywordsIn vivoRadiation therapyCancerCancer researchIn vitroMedicineOvarian cancerCancer cellHead and neck cancerLung cancerRadiosensitizerPharmacologyOncologyBiologyInternal medicineBiochemistryGenetics

Abstract

fetched live from OpenAlex

There is a compelling need to develop anticancer therapies that target cancer cells and tissues. Arising from innovative femtomedicine studies, a new class of non-platinum-based halogenated molecules (called FMD molecules) that selectively kill cancer cells and protect normal cells in treatments of multiple cancers has been discovered. This article reports the first observation of the radiosensitizing effects of such compounds in combination with ionizing radiation for targeted radiotherapy of a variety of cancers. We present in vitro and in vivo studies focused on combination with radiotherapy of cervical, ovarian, head and neck, and lung cancers. Our results demonstrate that treatments of various cancer cells in vitro and in vivo mouse xenograft models with such compounds led to enhanced efficiencies in radiotherapy, while the compounds themselves induced no or little radiotoxicity toward normal cells or tissues. These compounds are therefore effective radiosensitizers that can be translated into clinical trials for targeted radiotherapy of multiple types of cancer. This study also shows the potential of femtomedicine to bring breakthroughs in understanding fundamental biologic processes and to accelerate the discovery of novel drugs for effective treatment or prevention of a variety of cancers. Mol Cancer Ther; 15(4); 640-50. ©2016 AACR.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.078
Threshold uncertainty score0.666

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.024
GPT teacher head0.311
Teacher spread0.287 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations13
Published2016
Admission routes2
Has abstractyes

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